Article Text
PDF
Abstract
Background Routine health information system(s) (RHIS) facilitate the collection of health data at all levels of the health system allowing estimates of disease prevalence, treatment and preventive intervention coverage, and risk factors to guide disease control strategies. This core health system pillar remains underdeveloped in many low-income and middle-income countries. Efforts to improve RHIS data coverage, quality and timeliness were launched over 10 years ago.
Methods A systematic review was performed across 12 databases and literature search engines for both peer-reviewed articles and grey literature reports on RHIS interventions. Studies were analysed in three stages: (1) categorisation of RHIS intervention components and processes; (2) comparison of intervention component effectiveness and (3) whether the post-intervention outcome improved above the WHO integrated disease surveillance response framework data quality standard of 80% or above.
Results 5294 references were screened, resulting in 56 studies. Three key performance determinants—technical, organisational and behavioural—were proposed as critical to RHIS strengthening. Seventy-seven per cent [77%] of studies identified addressed all three determinants. The most frequently implemented intervention components were ‘providing training’ and ‘using an electronic health management information systems’. Ninety-three per cent [93%] of pre–post or controlled trial studies showed improvements in one or more data quality outputs, but after applying a standard threshold of >80% post-intervention, this number reduced to 68%. There was an observed benefit of multi-component interventions that either conducted data quality training or that addressed improvement across multiple processes and determinants of RHIS.
Conclusion Holistic data quality interventions that address multiple determinants should be continuously practised for strengthening RHIS. Studies with clearly defined and pragmatic outcomes are required for future RHIS improvement interventions. These should be accompanied by qualitative studies and cost analyses to understand which investments are needed to sustain high-quality RHIS in low-income and middle-income countries.
- epidemiology
- health systems
- systematic review
- public health
Data availability statement
Data are available on request. All data relevant to the study are included in the article or uploaded as online supplemental information. The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
Statistics from Altmetric.com
Data availability statement
Data are available on request. All data relevant to the study are included in the article or uploaded as online supplemental information. The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
Supplementary materials
Supplementary Data
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
Footnotes
Handling editor Edwine Barasa
Twitter @justinparkhurst
Contributors JL conducted the study and drafted the manuscript; NAE supervised the study and guided the writing of the manuscript and was part of the study selection of studies between October 2017 and January 2021; CAL conceived the paper, supported the data analysis and supported the drafting of the manuscript and was part of the study selection of studies between October 2017 and January 2021; LOH was the second reviewer during the study selection; RWS supported the drafting of the discussions section; NDH was part of the study selection of studies in January 2021, JP and JW reviewed and revised the manuscript. All authors read, reviewed and approved the final manuscript.
Funding Support for this work was provided by the UK’s Department for International Development (DFID) for their continued support to a project Strengthening the Use of Data for Malaria Decision Making in Africa (DFID Programme Code 203155) that provided support to JL, CAL, LOH and NAE. RWS is funded by Wellcome Trust Principal Fellowship (number 103602 and 212176) and acknowledges the support of the Wellcome Trust to the Kenya Major Overseas Programme (number 203077).This research is also supported by funding from MSD, through its MSD for Mothers programme. MSD has no role in the design, collection, analysis, and interpretation of data, in the writing of manuscripts, or in decisions to submit manuscripts for publication. The content of all publications is solely the responsibility of the authors and does not represent the official views of MSD. MSD for Mothers is an initiative of Merck & Co., Inc., Kenilworth, N.J., U.S.A
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.